Modern cybersecurity operations depend on fast, reliable data movement across cloud, on-premises and hybrid environments. Security teams collect data from security information and event management ...

Embodied AI world models drew $6 billion in Q1 2026 alone, but new analysis from Fusion Fund investors argues the LLM scaling analogy has a structural flaw: unlike text, the physical world has no ...

Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...

Public experiment log using Get Physics Done (GPD) with Codex to explore predictive control of tokamak plasma turbulence and confinement. A physics-based flight simulator for optimizing airbrake ...

Marc Santos is a Guides Staff Writer from the Philippines with a BA in Communication Arts and over six years of experience in writing gaming news and guides. He plays just about everything, from ...

Abstract: Model-free predictive control (MFPC) has become a popular choice for addressing the robustness limitations of model-based predictive control (MBPC), by replacing physical models with ...

do-mpc is a comprehensive open-source toolbox for robust model predictive control (MPC) and moving horizon estimation (MHE). do-mpc enables the efficient formulation and solution of control and ...

To drive growth, companies should transform customer support from reactive to predictive and proactive. Using foresight, ethical data and strategic alignment can turn customer experience into a key ...